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Game design feature prioritization

Skill Stanestane/game-design-skills-bundle/game-design-feature-prioritization

A public OpenClaw and ClawHub-ready bundle of game design skills for emotional direction, feature workflows, audits, FTUE, pitch decks, prototyping, and red-team design review.

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npx -y skills add Stanestane/game-design-skills-bundle --skill game-design-feature-prioritization

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Prioritize game design feature options by comparing expected impact, implementation cost, strategic fit, and roadmap context. Use when choosing between competing feature ideas, deciding what to do now versus later, ranking solution paths after ideation, or identifying which option is best immediately and which is better long-term.

SKILL.md

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Game Design Feature Prioritization

Choose the strongest next move, not just the loudest idea.

Use this skill to compare candidate features or solution paths and decide what should happen now, later, or not at all. Keep the process practical. Rough structured judgment is better than fake precision, but explicit comparison is still useful.

Read references/family-conventions.md when you need the shared conventions for this GROW-derived skill family.

What to produce

Generate:

  1. Candidate list - what is being prioritized
  2. Evaluation matrix - impact, cost, fit, risk, timing
  3. Priority ranking - now, later, discard, or monitor
  4. Recommendation - what should happen next and why

Process

1. List the candidates

Make sure the compared items are clear and meaningfully distinct.

2. Score the options

Use rough structured scoring such as 1-5 for:

  • Impact - expected player or business value
  • Implementation cost - time, resources, complexity
  • Strategic fit - alignment with game direction and roadmap
  • Risk - uncertainty, dependency burden, fragility
  • Timing - whether this is right now or later

3. Interpret in context

Do not choose purely by raw score. Also consider:

  • roadmap sequencing
  • enabling value for future features
  • opportunity cost
  • whether a slightly weaker option is smarter in the long run

4. Recommend action

For each option, classify it as:

  • Do now
  • Test first
  • Do later
  • Discard for now

Response structure

Candidates

  • ...

Evaluation Matrix

OptionImpactCostStrategic FitRiskTimingNotes

Priority Ranking

  • ...

Recommendation

  • ...

Fast mode

  • What are we choosing between?
  • Which option has the best impact-to-cost profile?
  • Which option best fits the roadmap right now?
  • What should we do now, later, or not at all?

Working principle

The locally optimal choice is not always the strategically best one.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.